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🔭 LLM Observability

Tracing, evaluation and monitoring platforms for AI apps in production.

Best LLM observability tools in 2026 — our verdict

Once your AI app hits production, you need tracing, evals and cost monitoring — prompt-and-pray doesn't scale. Langfuse is the leading open-source option with a generous self-host path, LangSmith is the natural fit if you already build on LangChain, Helicone is the fastest way to add observability via a proxy, Braintrust excels at evals-driven development, and Arize Phoenix plus LangWatch round out strong open-source and EU-friendly choices.

Pricing here is usage-based and can surprise you: trace volume, retention windows and seat counts all move the bill. Start with a free tier on real production traffic, measure your trace volume, then compare. Our Langfuse vs LangSmith and LangSmith alternative guides break down the decision in detail.

💡 How we picked these

We signed up for each tool's free tier, ran identical test tasks, and ranked them on output quality, ease of use, pricing fairness and free-tier generosity. Prices change often — always confirm on the official site before buying.